--- title: "MenakBERT — Hebrew Diacriticizer — Cohen 2024" description: "The task is to add niqqud to plain Hebrew. 8 references, cited by 2 papers here." authors: ["Ido Cohen", "Jacob Gidron", "Idan Pinto"] year: 2024 venue: "arXiv:2410.02417" source: "https://arxiv.org/abs/2410.02417" arxiv: "2410.02417" licence: "arXiv non-exclusive distribution licence (read only, no redistribution)" licence_url: "http://arxiv.org/licenses/nonexclusive-distrib/1.0/" summary_licence: "Elamur Cosmic License" canonical: "https://research.elamur.ai/free/en/papers/cohen-2024-menakbert-hebrew-diacriticizer/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/cohen-2024-menakbert-hebrew-diacriticizer/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [2024](https://md.research.elamur.ai/free/en/papers/2024/page/5/) / MenakBERT — Hebrew Diacriticizer # MenakBERT — Hebrew Diacriticizer **Authors:** [Ido Cohen](https://md.research.elamur.ai/free/en/authors/ido-cohen/), [Jacob Gidron](https://md.research.elamur.ai/free/en/authors/jacob-gidron/) and Idan Pinto · **Year:** 2024 · **Venue:** arXiv 2410.02417 (Tel Aviv University student paper) **Link:** [arxiv.org/abs/2410.02417](https://arxiv.org/abs/2410.02417) · **Licence:** copyrighted — summary only (arXiv non-exclusive licence) [**0** citations](https://openalex.org/works?filter=cites:W4403883901) OpenAlex, 2026-10-14 · [**2** citations in our library](https://md.research.elamur.ai/free/en/papers/cohen-2024-menakbert-hebrew-diacriticizer/cited-by/) of the 140,884 papers whose bibliographies we read · [arXiv:2410.02417](https://openalex.org/S4306400194) · [licence](http://arxiv.org/licenses/nonexclusive-distrib/1.0/) - [Publisher's page](https://arxiv.org/abs/2410.02417) - [PDF](https://arxiv.org/pdf/2410.02417) - [arXiv 2410.02417](https://arxiv.org/abs/2410.02417) - [OpenAlex](https://openalex.org/W4403883901) **Authors (3)** 1. [Ido Cohen](https://openalex.org/A5102000230) [ORCID](https://orcid.org/0009-0008-9187-0840) · [Semantic Scholar](https://www.semanticscholar.org/author/2113905042) · h 3 · 59 citations · 8 works 2. [Jacob Gidron](https://openalex.org/A5009457488) [Semantic Scholar](https://www.semanticscholar.org/author/2187208232) · h 2 · 50 citations · 4 works 3. [Idan Pinto](https://openalex.org/A5033091620) [ORCID](https://orcid.org/0000-0003-4109-9564) · [Semantic Scholar](https://www.semanticscholar.org/author/2213145525) · h 0 · 0 citations · 8 works Citations and author metrics: OpenAlex, 2026-10-14; authors with the same name are not always told apart. ## What it is about The task is to add niqqud to plain Hebrew. Following Nakdimon, the marks are split into three decisions per letter: the shin/sin dot, the dagesh, and the vowel. The authors fine-tune TavBERT, a character-level BERT pretrained on 3.1 billion Hebrew words, with three output heads, on Nakdimon's data (2.6 million premodern and 0.3 million modern characters), trained in chronological order so the model ends on modern text. On Nakdimon's test set it scores 98.82% decision accuracy and 94.12% word accuracy, close to Dicta's rule-assisted Nakdan (98.94 / 95.83) and above Nakdimon. Errors include verb/adjective homographs, the definite article hidden in the vowel of a prefixed preposition (וּבָרְכוּשׁ vs וּבִרְכוּשׁ), and foreign names; a model fine-tuned for dotting also transfers to POS tagging. ## For Mova - I1. The three-way split of the pointing (shin/sin dot, dagesh, vowel) is a clean way to describe what the marks do: use it in the script chapter, and in any Mova check of pointed text count errors per category. - I2. The hidden article: after בְּ/כְּ/לְ the article shows only in the prefix's vowel and the following dagesh. Check on the Torah trees that every such case gets `Definite=Def`, and state the rule (pataḥ/qameṣ + dagesh after the prefix = article) in the noun chapter. - I3. The four scores DEC/CHA/WOR/VOC (decision, character, word, and "pronounced right") are the standard for a vocaliser; reuse them if Mova ever vocalises Mishnaic or unpointed text. Mova's Torah is already pointed, so the model itself is not needed. I1 goes to [languages/hbo/01-script.md](https://mova.elamur.ai/free/en/docs/languages/hbo/01-script/); I2 is a check in `tools/macula` (FEATS) and a point in `04-noun.md` (the article); I3 is the scoring for any future vocaliser, described in `13-mova-tools.md`. ## Institutions [🎓**Tel Aviv University** Tel Aviv · Israel 54 works · 7,966 citations](https://md.research.elamur.ai/free/en/universities/tel-aviv-university/) Topics[Hebrew & Aramaic](https://md.research.elamur.ai/free/en/topics/hebrew-aramaic/) · [Semitic languages](https://md.research.elamur.ai/free/en/topics/semitic-languages/) ## Cite Cite as Ido Cohen, Jacob Gidron and Idan Pinto. 2024. MenakBERT — Hebrew Diacriticizer. arXiv:2410.02417. The paper itself, not this card. BibTeX from the library's record of the work. [arXiv 2410.02417](https://arxiv.org/abs/2410.02417) ```bibtex @misc{cohen2024menakbert, title = {{MenakBERT — Hebrew Diacriticizer}}, author = {Ido Cohen, Jacob Gidron and Idan Pinto}, year = {2024}, eprint = {2410.02417}, archivePrefix = {arXiv}, url = {https://arxiv.org/abs/2410.02417} } ``` - [← previous Improving Low-Resource Machine Translation via Cross-Linguistic Transfer from Typologically Similar High-Resource Languages](https://md.research.elamur.ai/free/en/papers/boujkian-2024-improving-low-resource-machine-translation/) - [next → Normalizing without Modernizing: Keeping Historical Wordforms of Middle French while Reducing Spelling Variants](https://md.research.elamur.ai/free/en/papers/rubino-2024-normalizing-without-modernizing-keeping-historical/) - [↑ back to papers of 2024](https://md.research.elamur.ai/free/en/papers/2024/page/5/) ## References 8 references, 6 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet. 1. Ya’akov Gal. 2002. An HMM approach to vowel restoration in Arabic and Hebrew. In Proceedings of the ACL-02 Workshop on Computational Approaches to Semitic Languages, Philadelphia, Pennsylvania, USA. Association for Computational Linguistics. [our card](https://md.research.elamur.ai/free/en/papers/gal-2002-hmm-approach-vowel-restoration-arabic/) 2. Leonid Kontorovich. 2001. Problems in semitic nlp: Hebrew vocalization using hmms. [find](https://scholar.google.com/scholar?q=Leonid+Kontorovich%2E+2001%2E+Problems+in+semitic+nlp%3A+Hebrew+vocalization+using+hmms%2E) 3. Avi Shmidman, Shaltiel Shmidman, Moshe Koppel, and Yoav Goldberg. 2020. Nakdan: Professional Hebrew diacritizer. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pages 197– 203, Online. Association for Computational Linguistics. [our card](https://md.research.elamur.ai/free/en/papers/shmidman-2020-nakdan-professional-hebrew-diacritizer/) 4. Elazar Gershuni, Yuval Pinter. 2021. Restoring Hebrew Diacritics Without a Dictionary (Nakdimon). [our card](https://md.research.elamur.ai/free/en/papers/gershuni-2022-restoring-hebrew-diacritics-without-dictionary/) 5. Omri Keren, Tal Avinari, Reut Tsarfaty, Omer Levy. 2022. Breaking Character: Are Subwords Good Enough for MRLs After All? [find](https://scholar.google.com/scholar?q=Omri+Keren%2C+Tal+Avinari%2C+Reut+Tsarfaty%2C+Omer+Levy%2E+2022%2E+Breaking+Character%3A+Are+Subwords+Good+Enough+for+MRLs+After+All%3F) 6. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. 2018. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Mandar Joshi, Danqi Chen, Yinhan Liu, Daniel S. [our card](https://md.research.elamur.ai/free/en/papers/devlin-2019-bert-pre-training-deep-bidirectional/) 7. Weld, Luke Zettlemoyer, Omer Levy. 2020. SpanBERT: Improving Pre-training by Representing and Predicting Spans. [our card](https://md.research.elamur.ai/free/en/papers/joshi-2019-spanbert-improving-pre-training-representing/) 8. Shoval Sade, Amit Seker, and Reut Tsarfaty. 2018. The Hebrew Universal Dependency treebank: Past present and future Amit Seker and Reut Tsarfaty. 2020. A pointer network architecture for joint morphological segmentation and tagging [our card](https://md.research.elamur.ai/free/en/papers/seker-2020-pointer-network-architecture-joint-morphological/)